Comparing Machine Learning and Deep Learning Approaches to Diagnose Epilepsy Disease

S Salehzehi, E Irankhah, M Sabet - … of the 3rd International Conference on …, 2023 - Springer
Even though, epilepsy is recognized as a component of brain disease, and seizures in these
diseases vary from person to person. This study aimed to implement some procedures …

Comparative Analysis of Deep Learning Models for the Detection of Epileptic Seizure

B Arshad, A Mukherjee - American Journal of Advanced …, 2023 - ingentaconnect.com
Electroencephalogram (EEG) is used to detect epilepsy, a common neurological disorder.
Neurologists visually examine EEG results to make the diagnosis. Researchers have …

Automated detection of Epilepsy EEG based on Hybrid Model of CNN and LSTM

X Wang, J Zhang, X Huang, Z Ma - Available at SSRN 4065237, 2022 - papers.ssrn.com
Background: Automatic detecting methods for the detection of non-stationary and non-
invasive epileptic EEGs are essential tools in neurological research. Traditional machine …

Epileptic seizures detection on EEG signal using deep learning techniques

D Sagga, A Echtioui, R Khemakhem… - … for Signal and …, 2022 - ieeexplore.ieee.org
Epilepsy is a chronic brain disease that affects a large percentage of the psychiatric
population, and its progression can be fatal. It is a major public health problem as well as a …

Advancing Epilepsy Disease Classification through Machine Learning and Deep Learning Models Utilizing EEG Data.

A Saleem, MA Khan, HM Yousaf - 2023 17th International …, 2023 - ieeexplore.ieee.org
Epilepsy disease is a neurological condition marked by recurring seizures that has a big
effect on people's life. Effective management and therapy depend on a prompt and correct …

Comprehensive survey of deep learning applications in the diagnosis of epilepsy

A Ticku, S Gupta - … Technology for Competitive Strategies (ICTCS 2022) …, 2023 - Springer
The human brain is a complex structure where we have innumerable neurons connected to
each other, passing signals from one part of the body to another. Normally, signals are …

Diagnosis of epilepsy disease with deep learning methods using EEG signals

Y Geniş, EA Aydin - 2022 30th Signal Processing and …, 2022 - ieeexplore.ieee.org
Analysis and classification of electroencephalogram (EEG) signals are so important in the
diagnosis of epilepsy disease caused by abnormal changes in the electrical activity of the …

Epileptic seizure detection using LSTM: A deep learning technique

D Acharya, R Bhatia, A Gowreddygari, V Shaju… - Soft Computing for …, 2021 - Springer
Epilepsy is one of the most devastating diseases in the history of mankind. It is a
neurological disorder in which irregular transmission of brainwaves results in seizures …

Epileptic seizures classification based on deep neural networks

A Swetha, AK Sinha - Proceedings of the International Conference on …, 2021 - Springer
Epileptic seizure is a chronic and non-communicable disease which occurs in people of all
ages. In the detection of epileptic seizures, electroencephalography (EEG) plays a vital role …

An efficient comparison on machine learning and deep neural networks in epileptic seizure prediction

R Roseline Mary, BSE Zoraida… - Congress on Intelligent …, 2022 - Springer
Electroencephalography signals have been widely used in cognitive neuroscience to
identify the brain's activity and behavior. These signals retrieved from the brain are most …